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Transforming clinical trials: the emerging roles of large language models.
Ghim, Jong-Lyul; Ahn, Sangzin.
Afiliação
  • Ghim JL; Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan 47392, Korea.
  • Ahn S; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea.
Transl Clin Pharmacol ; 31(3): 131-138, 2023 Sep.
Article em En | MEDLINE | ID: mdl-37810626
Clinical trials are essential for medical research, but they often face challenges in matching patients to trials and planning. Large language models (LLMs) offer a promising solution, signaling a transformative shift in the field of clinical trials. This review explores the multifaceted applications of LLMs within clinical trials, focusing on five main areas expected to be implemented in the near future: enhancing patient-trial matching, streamlining clinical trial planning, analyzing free text narratives for coding and classification, assisting in technical writing tasks, and providing cognizant consent via LLM-powered chatbots. While the application of LLMs is promising, it poses challenges such as accuracy validation and legal concerns. The convergence of LLMs with clinical trials has the potential to revolutionize the efficiency of clinical trials, paving the way for innovative methodologies and enhancing patient engagement. However, this development requires careful consideration and investment to overcome potential hurdles.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article